Literature DB >> 26433562

Predictors of outcome from computer-based treatment for substance use disorders: Results from a randomized clinical trial.

Sunny Jung Kim1, Lisa A Marsch2, Honoria Guarino3, Michelle C Acosta4, Yesenia Aponte-Melendez5.   

Abstract

BACKGROUND: Although empirical evidence for the effectiveness of technology-mediated interventions for substance use disorders is rapidly growing, the role of baseline characteristics of patients in predicting treatment outcomes of a technology-based therapy is largely unknown.
METHOD: Participants were randomly assigned to either standard methadone maintenance treatment or reduced standard treatment combined with the computer-based therapeutic education system (TES). An array of demographic and behavioral characteristics of participants (N=160) was measured at baseline. Opioid abstinence and treatment retention were measured weekly for a 52-week intervention period. Generalized linear model and Cox-regression were used to estimate the predictive roles of baseline characteristics in predicting treatment outcomes.
RESULTS: We found significant predictors of opioid abstinence and treatment retention within and across conditions. Among 21 baseline characteristics of participants, employment status, anxiety, and ambivalent attitudes toward substance use predicted better opioid abstinence in the reduced-standard-plus-TES condition compared to standard treatment. Participants who had used cocaine/crack in the past 30 days at baseline showed lower dropout rates in standard treatment, whereas those who had not used exhibited lower dropout rates in the reduced-standard-plus-TES condition.
CONCLUSIONS: This study is the first randomized controlled trial, evaluating over a 12-month period, how various aspects of participant characteristics impact outcomes for treatments that do or do not include technology-based therapy. Compared to standard alone treatment, including TES as part of the care was preferable for patients who were employed, highly anxious, and ambivalent about substance use and did not produce worse outcomes for any subgroups of participants.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Behavioral therapy; Opioid dependence; Participant characteristics; Randomized controlled trial; Technology-delivered intervention

Mesh:

Substances:

Year:  2015        PMID: 26433562      PMCID: PMC4663155          DOI: 10.1016/j.drugalcdep.2015.09.019

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  23 in total

Review 1.  Co-occurring mental and substance abuse disorders: a review on the potential predictors and clinical outcomes.

Authors:  Pablo Najt; Paolo Fusar-Poli; Paolo Brambilla
Journal:  Psychiatry Res       Date:  2010-08-21       Impact factor: 3.222

2.  Computer-based brief motivational intervention for perinatal drug use.

Authors:  Steven J Ondersma; Sara K Chase; Dace S Svikis; Charles R Schuster
Journal:  J Subst Abuse Treat       Date:  2005-06

3.  Predictors of outcome in LAAM, buprenorphine, and methadone treatment for opioid dependence.

Authors:  Lisa A Marsch; Mary Ann Chutuape Stephens; Timothy Mudric; Eric C Strain; George E Bigelow; Rolley E Johnson
Journal:  Exp Clin Psychopharmacol       Date:  2005-11       Impact factor: 3.157

4.  Predictors of substance use among black urban adolescents with asthma: a longitudinal assessment.

Authors:  Jerren C Weekes; Sian Cotton; Meghan E McGrady
Journal:  J Natl Med Assoc       Date:  2011-05       Impact factor: 1.798

5.  A Web-Based Behavior Therapy Program Influences the Association Between Cognitive Functioning and Retention and Abstinence in Clients Receiving Methadone Maintenance Treatment.

Authors:  Michelle C Acosta; Lisa A Marsch; Haiyi Xie; Honoria Guarino; Yesenia Aponte-Melendez
Journal:  J Dual Diagn       Date:  2012-10

Review 6.  Effectiveness and cost-effectiveness of computer and other electronic aids for smoking cessation: a systematic review and network meta-analysis.

Authors:  Y-F Chen; J Madan; N Welton; I Yahaya; P Aveyard; L Bauld; D Wang; A Fry-Smith; M R Munafò
Journal:  Health Technol Assess       Date:  2012       Impact factor: 4.014

Review 7.  Outcome predictors in substance use disorders.

Authors:  Domenic A Ciraulo; Joanna Piechniczek-Buczek; E Nalan Iscan
Journal:  Psychiatr Clin North Am       Date:  2003-06

8.  Computerized behavior therapy for opioid-dependent outpatients: a randomized controlled trial.

Authors:  Warren K Bickel; Lisa A Marsch; August R Buchhalter; Gary J Badger
Journal:  Exp Clin Psychopharmacol       Date:  2008-04       Impact factor: 3.157

9.  Attitudes toward technology-based health information among adult emergency department patients with drug or alcohol misuse.

Authors:  Esther K Choo; Megan L Ranney; Zerlina Wong; Michael J Mello
Journal:  J Subst Abuse Treat       Date:  2012-12

Review 10.  eHealth Literacy: Essential Skills for Consumer Health in a Networked World.

Authors:  Cameron D Norman; Harvey A Skinner
Journal:  J Med Internet Res       Date:  2006-06-16       Impact factor: 5.428

View more
  5 in total

Review 1.  Opioid agonist treatment for people who are dependent on pharmaceutical opioids.

Authors:  Suzanne Nielsen; Wai Chung Tse; Briony Larance
Journal:  Cochrane Database Syst Rev       Date:  2022-09-05

2.  Can persons with a history of multiple addiction treatment episodes benefit from technology delivered behavior therapy? A moderating role of treatment history at baseline.

Authors:  Sunny Jung Kim; Lisa A Marsch; Michelle C Acosta; Honoria Guarino; Yesenia Aponte-Melendez
Journal:  Addict Behav       Date:  2015-11-26       Impact factor: 3.913

3.  Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data.

Authors:  Sunny Jung Kim; Lisa A Marsch; Jeffrey T Hancock; Amarendra K Das
Journal:  J Med Internet Res       Date:  2017-10-31       Impact factor: 5.428

4.  Harnessing Facebook for Smoking Reduction and Cessation Interventions: Facebook User Engagement and Social Support Predict Smoking Reduction.

Authors:  Sunny Jung Kim; Lisa A Marsch; Mary F Brunette; Jesse Dallery
Journal:  J Med Internet Res       Date:  2017-05-23       Impact factor: 5.428

Review 5.  Retention Strategies for Medications for Opioid Use Disorder in Adults: A Rapid Evidence Review.

Authors:  Brian Chan; Emily Gean; Irina Arkhipova-Jenkins; Jennifer Gilbert; Jennifer Hilgart; Celia Fiordalisi; Kimberly Hubbard; Irene Brandt; Elizabeth Stoeger; Robin Paynter; Philip Todd Korthuis; Jeanne-Marie Guise
Journal:  J Addict Med       Date:  2021 Jan-Feb 01       Impact factor: 4.647

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.